Mathematical methods in systematic conservation planning (SCP) represent a significant step toward cost-effective, transparent allocation of resources for biodiversity conservation. However, research demonstrates important consequences of uncertainties in SCP. Current research often relies on simplified case studies with unknown forms and amounts of uncertainty and low statistical power for generalizing results. Consequently, conservation managers have little evidence for the true performance of conservation planning methods in their own complex, uncertain applications. SCP needs to build evidence for predictive models of error and robustness to multiple, simultaneous uncertainties across a wide range of problems of known complexity. Only then can we determine true performance rather than how a method appears to perform on data with unknown uncertainty